Look up the sales-tax rate for a region from built-in tables and, if an amount is given, compute net/tax/gross. Pure; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| amount | No | Optional amount to compute tax on | |
| region | Yes | Region key with a sales-tax rate on file (e.g. US-CA) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It states 'Pure' (no side effects) and 'price 0.0 (free)' (cost), and 'from built-in tables' (no external data). These are useful behavioral traits beyond the schema. However, it does not mention error cases, return format, or rate interpretation details, which keeps it from a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences: the first states the core functionality, the second adds cost and purity. No fluff, front-loaded with the primary action, and every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (two params, one optional, no output schema). The description covers what it does, side-effect behavior, and cost. It does not explain the exact output structure (e.g., names of net/tax/gross fields or rate format), but given the simplicity and the schema covering parameters, it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both 'region' and 'amount' have descriptive text. The description adds a conditional behavior ('if an amount is given, compute net/tax/gross') that relates to the amount parameter but does not provide further parameter-level detail beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('look up') and resource ('sales-tax rate for a region'), and adds the conditional computation of net/tax/gross. This clearly distinguishes it from siblings like fx_tax_vat_calc (VAT) and fx_tax_list_rates (listing rates), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: look up a sales-tax rate for a region and optionally compute amounts. It does not explicitly state when to use this tool versus alternatives such as fx_tax_vat_calc or fx_tax_list_rates, nor does it provide exclusions or prerequisites. The context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, especially the ledger-watch groups with domain prefixes. However, there are near-duplicate utilities such as content_authenticity_domain_reputation and domain_intel_reputation, and fx_tax_convert overlaps with price_oracle_fx_rate/convert. The sheer number of tools also increases the chance of selecting the wrong one, though descriptions are generally clear.
The naming is largely consistent with a <domain>_<action> or <domain>_<watch>_<action> pattern, and all names use snake_case. Minor deviations include standalone names like entity_search, kyb_report, verify_receipt, and the confusing singular/plural pair of sanction_watch_* and sanctions_screen_*. Overall, the pattern is predictable.
With 172 tools, this server is far beyond the typical well-scoped range. It bundles dozens of unrelated utility domains (weather, carbon, CVE, geo, etc.) alongside the Japan public-ledger watches, making it unwieldy for an agent to navigate. This extreme count is a major coherence problem.
For the core Japan public-ledger domain, coverage is excellent: each ledger has search, get, timeline, recent_changes, and verify_ledger, plus cross-ledger entity_search and temporal_query. The unrelated utility areas are also fairly complete for their own purposes, but the server's scope is so broad that some utilities are duplicated (e.g., multiple currency converters). Overall, no critical dead ends in the main domain.